Recent advances in video processing technologies have led to a surge in popularity of new video processing applications that make powerful video editing capabilities available to a wide base of users. Typically, video processing applications allow users to download and upload video and audio segments, as well as edit and manipulate these segments for producing a cohesive video or movie.
In performing such tasks, video processing applications often use a video capture card to capture and store video segments onto the hard drive of a computer system. Video capture cards typically employ a coder/decoder (also called a “CODEC”) to compress the video with a compression standard such as Motion-JPEG, DV, MPEG-1, MPEG-2, etc. Many digital video storage formats store pixel data in a luminance and chrominance colorspace often referred to Y/Cr/Cb (also referred to as YUV). In a luminance and chrominance colorspace three components are stored for each pixel: one for luminance (Y) and two for color information (Cr and Cb). Most computer display systems store pixel information in an RGB format that also contains three components per pixel, one each for the Red (R), Green (G), and Blue (B) portions of the color. Pixel information stored in either YUV or RGB format can be converted to the other format using straightforward matrix mathematics.
In the DV (digital video) storage format, storage is typically accomplished with an 8-bit luminance (Y) value for each pixel. 8 bits allows luminance (Y) values ranging from 0 through 255. In 8-bit digital video, black is typically encoded at Y=16 and white is encoded at Y=235. The luminance values from 1 to 15, referred to as footroom, and 236 to 254, referred to as headroom, are used to accommodate ringing and overshoot in a signal. Industry standard equations (such as those specified by Rec. ITU R BT-601) can convert 8-bit RGB encoded images with RGB values ranging from 0 to 255 into YUV encoded images with luminance (Y) values ranging from 16 to 235. Most software DV CODECs follow this mapping so that a use may translate, say, naturalistic computer pictures into quality video.
However, there are several phenomena which may contribute to degradation or compromising of the dynamic range of given colors in a resulting video segment. For example, difficulties often arise, for example, because cameras can often capture values that are superwhite (values resulting from specular reflections, sun, or bright lights, clouds or white walls). Superwhite values may exceed the nominal white value of 235 as registered on a waveform monitor, where these whites may peak at 100 IRE (NTSC) which is the brightest value allowable on a broadcast RF modulator. In the YUV space, the Y values range from 235 to 254; but on a waveform monitor, whites can be seen to range from 100 IRE to almost 110 IRE, all of which represent illegal values (e.g., Y values above 254), and are accordingly clipped to 254 by a CODEC when converting to RGB, thereby compromising the dynamic range of at least the white value in a given digital image.
Typically, users may attempt to mitigate such value degradation by employing color correction of the RGB space. A problem arises, however, because color correction, still yield only a limited amount of headroom for colors (such as superwhite), and also require extensive operations cycles, execution time, and memory access in computer systems that support digital video processing applications. Inherent in such a problem is the need for rendering, where editing is translated and stored on the hard drive a computer system supporting a given video image processing application. Even recently developed “real time” systems still need to go back to rendering in cases where a user simultaneously color corrects, adds filters, effects, and superimposes graphics, even for a high end real time system, the capacity will be overwhelmed and the real time performance will be compromised. As such, there are still deficiencies not addressed by recent advances in video processing, which in particular concerns the limited overhead on color values and a less expensive approach to color correction.